The importance of considering contextual probabilities in shaping response patterns within psychological testing is underscored, despite the ubiquitous nature of order effects discussed extensively in methodological literature. Drawing from concepts such as path-dependency, first-order autocorrelation, state-dependency, and hysteresis, the present study is an attempt to address how earlier responses serve as an anchor for subsequent answers in tests, surveys, and questionnaires. Introducing the notion of non-commuting observables derived from quantum physics, I highlight their role in characterizing psychological processes and the impact of measurement instruments on participants' responses. We advocate for the utilization of first-order Markov chain modeling to capture and forecast sequential dependencies in survey and test responses. The employment of the first-order Markov chain model lies in individuals' propensity to exhibit partial focus to preceding responses, with recent items most likely exerting a substantial influence on subsequent response selection. This study contributes to advancing our understanding of the dynamics inherent in sequential data within psychological research and provides a methodological framework for conducting longitudinal analyses of response patterns of test and questionnaire.

该研究旨在探讨早期回答如何影响测试、调查和问卷调查中后续答案的锚定作用，介绍了来自量子物理学的非交换可观测物的概念，并倡导利用一阶马尔科夫链模型来捕捉测试和调查回答中的顺序依赖关系，以此推进我们对心理研究中序列数据固有动态的理解，并为测试和问卷调查的纵向分析提供了一个方法学框架。

心理测量中响应动态的马尔可夫链模型